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Ethical AI and Data PrivacyhardMultiple ChoiceObjective-mapped

AI Associate Ethical AI and Data Privacy Practice Question

A company uses Einstein Discovery to build a model that predicts customer lifetime value. They want to ensure the model's decisions are auditable and that they can track the business impact of AI recommendations over time. What should they implement?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Audit trail

An audit trail logs when AI recommendations are made and whether they were followed, and can be used to track outcomes over time. This enables accountability and measurement of AI impact, supporting transparency and governance.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Score factors

    Why it's wrong here

    Score factors explain individual predictions but do not log actions or track impact over time.

  • Grounding

    Why it's wrong here

    Grounding ensures AI uses relevant CRM data, but does not provide logging or impact tracking.

  • Toxicity detection

    Why it's wrong here

    Toxicity detection is unrelated to auditability of business outcomes.

  • Audit trail

    Why this is correct

    An audit trail records when recommendations are made and acted upon, enabling analysis of AI impact on business outcomes over time.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.